Monte Carlo Simulations: Number of Iterations and Accuracy

Abstract

This report focuses on 2 related topics, the number of Monte Carlo iterations and the accuracy or error in the estimation of the mean of the probability distribution for the quantity of interest being analyzed. For most Monte Carlo simulations, it is the estimation of this mean that is desired. These 2 topics are related through the central limit theorem, and given one, the other can be determined when combined with the sample information for large sample sizes. Issues associated with small sample size have been mentioned and discussed in more detail for quantities of interest with a normal distribution.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2015
Accession Number
ADA621501

Entities

People

  • William Oberle

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Data Science
  • Demography
  • Errors
  • Information Science
  • Iterations
  • Monte Carlo Method
  • Normal Distribution
  • Probability
  • Probability Distributions
  • Random Variables
  • Simulations
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Samples
  • Statistical Tests

Fields of Study

  • Mathematics

Readers

  • Computational Fluid Dynamics (CFD)
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Regression Analysis.